Health disparities and disproportionate disease burdens among minorities and low socio-economic status (SES) groups typically focus on a single disease or condition. This study will address the related highly significant public health problem of disparities in diabetes comorbidities and multiple chronic conditions (MCC) that are leading causes of death (LCD). As death is the most serious health outcome, this investigation of specific diabetes MCC that are LCD addresses the critical barrier to progress in the area related to simply counting the number of chronic conditions and reporting the prevalence, which assumes all MCC have the same disease and financial burden. Scientific evidence is lacking regarding health disparities and the development and progression of specific diabetes-related MCC. This study's comprehensive and methodical approach provides evidence for NIDDK's strategic plan to address health disparities and disproportionate disease burdens among racial/ethnic minorities, low SES, and rural populations, along with the related financial burden of MCC. This is a large epidemiologic study, designed to evaluate all Michigan Medicare and adult Medicaid claims data. This study tests the following central hypothesis: For adults at high-risk for specific MCC that are LCD, participating in prevention/interventions is dependent upon a combination of SES, access to care, health behaviors, and other factors. The specific aims test the following hypotheses: (1) That certain MCC that are LCD are more prevalent and have higher healthcare costs than others. (2) That SES disparities exist, assessed as the independent association between specific MCC (e.g. LCD) and race/ ethnicity, gender, age, income, education. (3) That disparities in access to care exist, assessed as the association between specific MCC and outpatient ambulatory visits, emergency room visits, or hospitalizations; independent of rural residency and health insurance status. (4) That among high-risk Medicaid beneficiaries, SES disparities exist, assessed as the independent association between the longitudinal progression of diabetes to specific MCC (e.g. LCD) and race/ethnicity, gender, age, and access to care. This study will provide essential scientific data to better understand the choices and tradeoffs surrounding the expectation that healthcare providers should substitute social and economic goals derived from aggregate measures of health outcomes and costs, for their individual patient's needs. This proposal describes an innovative predictive modeling approach that develops and validates multivariable models, prior to using them to estimate an individual's probability of diabetes MCC. The results of this study have the potential to change the concepts that are currently driving this field of health disparities research, by providing healthcare providers, policymakers, and decision makers with scientific evidence for the development of data-driven evidence-based clinical pathways and policy changes directed toward highly significant, prevalent, and costly diabetes MCC. In addition, the student integration plan of this AREA award will enhance the research educational opportunities to benefit students and the university.